Meta: this was submitted with the article’s title “The CTF scene is dead” which I found very easy to understand. It has just been updated to use the subtitle’s first sentence, “Frontier AI has broken the open CTF format”. I find that much harder to grasp, rather like a garden-path sentence. My immediate thoughts were that “Frontier” was a company name, and that there was some file format named CTF. If you don’t know about Capture The Flag contests, the change doesn’t help. If you do, I think the change makes it worse.
If it helps I understand the second much better and feels less clickbaity and includes more info. I do agree with the points you made about the confusion although I find frontier a term used in this area a lot, “frontier AI models have” would probably resolve that.
If the title simply said "AI is out-performing humans at CTF" then none of this confusion exists. Nothing is "broken," we don't need to be superfluous with "frontier," and the point is still there.
But the article is arguing it is broken. That’s the point. You can disagree but that’s very much that the author is writing about, not a curiosity, and that it’s these top models that are not custom security models.
Imo frontier is too niche and specific, if you know what a frontier model means then it's fine, but if you don't then it's negative/detrimental to the title.
"new" does the same thing and is probably just a better descriptor then frontier
Replace ‘CTF’ with ‘high school’ or ‘university’ and you’ve described the total slow motion collapse of education; the only saving grace is that most of it requires in person presence.
We’ve figured out the human replacement pipeline it seems, but we haven’t figured out the eduction part. LLMs can be wonderful teachers, but the temptation to just tell it ‘do it for me’ is almost impossible to resist.
We are interviewing for a software dev role and we made the first round in person to prevent cheating. The gap between people who learned pre ai vs post is immense. I had a dev with supposedly 3 years experience and a degree in software who wouldn't have been able to write fizzbuzz without AI.
Can’t say you’re wrong but the last anecdote describes many I’ve had to review for jobs long before LLMs. Fizzbuzz is a classic thing that shockingly many devs genuinely cannot do, even at home.
Yeah, I've interviewed people like this 15 years ago. Degrees and experience mean nothing in this field. The best predictor I found was personal passion projects. Let them get as nerdy as possible, then you will see pretty quickly where their skills are at and what their limits are. And you will immediately filter out people who just studied CS because they heard you can make good money.
> I had a dev with supposedly 3 years experience and a degree in software who wouldn't have been able to write fizzbuzz without AI.
If you remove the "without AI" and the end, I've been hearing similar anecdotes about fizzbuzz for years (isn't the whole point of fizzbuzz to filter out those candidates?)
While this is true, it seems undeniable that if you use AI to do everything for you, you will never learn the skills. I'm seeing a massive amount of developers submitting stuff for review and admitting they have no idea how it works and they just generated it.
I had human teachers who did that in middle/high school. Took me many years to pick out all the hallucinated bits of "knowledge". I don't think the current models are any less reliable that what we currently have on average.
I'll always remember my middle school science teaching telling us that nuclear fusion violates conservation of mass because the 2 protons in a pair of hydrogen nuclei combine to make helium with 4 nucleons. It's not true, but that's not the point.
But he was a great teacher anyway. He was engaging and kept the kids in line and learning. I eventually learned the truth, and most of my classmates forgot about it. Teaching, like flying a plane or driving a train, might become more about keeping watch over a small group of people and ensuring that things don't go off the rails, and that's fine.
This one feels less sinister than some other things at least to me, personally. You can reasonably doubt that the conservation of mass is violated and find out the truth based on that. But understanding more complex biology or historical context for some things? Granted, many of these things seem to be low stakes, but I'm sure there are some there are not (sex ed comes to mind).
Yes, together with mass-energy equivalency it would form a coherent argument, and then also a correct one - but the thing is that if incomplete, it still might sound funky enough to you to research it if you care.
I think it helps that it's a very narrow field to look at, compared to fuzzy and big-picture view of social studies, for example. So much room to be confidently wrong... And sadly I can't think of a solution, LLMs or not.
Off the top of my head: DOMS being little crystals in muscles, tongue having separate areas for each type of taste, food pyramid, blue blood in the veins, the appendix being useless, body temperature doesn't change disregarding whether it's exposed to cold or to heat, and a whole lot of stuff related to politics and history I'd rather just omit (I don't live in the US).
All things I learned in school which were wrong information.
Not to mention, the current state of education is far worse. I don't think most realize how low the bar is.
They'll also encourage and praise you even when you're heading down the wrong path until you think you've uncovered the secret of the universe or proven that established science was wrong this whole time when really you've just been bullshitting with an engagement bot.
I think we should go a little deeper on this idea.
We can all agree that both human "experts" and LLMs can sometimes be right, and sometimes be confidently wrong.
But that doesn't imply that they're equally fit for purpose. It just means that we can't use that simple shortcut to conclude that one is inferior to the other.
I’ve always thought of the definition of “expert” as reliably knowing the difference between what is known, what is speculated but unproven, and what is unknown. People claim expertise in all sorts of things that they aren’t experts in. But true experts should not be wrong. They should qualify levels of certainty. This definition certainly works in the sciences.
I found this interview [0] on the subject of AI in CS education on the Oxide & Friends podcast very illuminating.
Of course, Brown University CS != All education, but interesting angle nevertheless.
A million times better than any human teacher I’ve ever had, for sure.
Now I’m certain that there exist those mythical human instructors who can do better, but that’s not worth much if 99.99% of people don’t have access to them. Just like a good human physician who takes their time with the patient is better than an LLM, but that’s not worth much either given that this doesn’t match most people’s experience with their own physicians.
Did an LLM teach you a topic you did not feel like learning?
For me the best human teachers were the ones that managed to make me interested on topics that I thought are boring/useless (many times my opinion being stupid, mostly due to lack of experience).
So far with LLM I learn about things I know something (at least that they exist) and I am interested in, which is a small subset of things that one should learn during lifetime.
Well I have some evidence to support your hypothesis. During Covid my kids were at home, eventually with some kind of self learning website from school. I was upstairs working, checking in with progress on the parents app. Finish your daily school work and then you can game.
The kids learnt all about Team Fortress 2, Roblox, Rainbow Six etc. They also learnt how to game the learning system so it looked like they were doing their work.
They can be incredible. One on one teaching with an infinitely patient teacher who can generate interactive problems on the fly, for dollars a month? Wild. A year of paid ChatGPT would pay for about 9 hours of cheap tutoring here.
Education is also figured out. You just need to learn, do and practice for yourself. Telling the agent "to just do it for you" is tempting, but it's not learning. You need to be deliberate when you're trying to actually learn and internalize.
Also, you could spin up your own educational agent with very strict instructions on guiding the user instead of just doing the work. Of course you can always go around it but if you're making an effort to learn, this is a good middle ground.
I was writing an obfuscator recently, I just had the model deobfuscate and optimize the code back to original and I kept improving the obfuscator until it couldn't. The funny thing is that after all this I also ended up with a really strong deobfuscator and optimizer which is probably more capable than most commercial tools.
The solution is just to make CTFs harder, but when do CTFs become too hard? Maybe the problem is that 'hard' CTFs are fundementally too 'simple' where it's just a logic chain and an exhaustive bruteforce towards a solution since there really are limited ways to express a solution in plain sight.
Or maybe human creativity has been exhausted and we're not so limitless as we thought. Only time will tell.
I had another idea spring to mind: we could hide two flags, one that could only be found by ai agents and not humans or tools written by humans.
bringing CTF solutions into the real world is a really good idea! I didn't even think of this until you mentioned it.
we have very powerful simulation tools so something like "project a pattern at these angles" wouldn't really work as you could simulate that.
I guess something cool is that we can make simulating the solution very expensive, but in real world it would be free since it's analog... As long as simulations take longer than it takes for a human to find a solution it would be a pretty good way to deal with it. I am sure people smarter than me can come up with something.
Maybe I was too early to dismiss human creativity.
Using real-life calculators to add? Calculate the Flag. I don't think it is dead at all. It's like mixing in board game / escape room / science / engineeer/ medical research elements.
Competitive programming scene always included offline competition and with AI they are becoming more important (and in general they were more fair even before). If CTFs are to survive, they should probably try to adopt this strategy.
You could even go so far that anything loaded on your computer is fair game, but not more than that (certain competitive programming competition for example allow unlimited amount of paper material - for CTFs you probably need much more than that, therefore electronic).
,,a beginner is pushed toward using AI before they have built the instincts the AI is replacing. That is an anti-pattern.''
The same article talks about CTF skills as a way to learn about security best practices and separately a sport.
In reality it was all about learning an extremely important skillset (securing/attacking software and systems) that is getting automated.
The real thing the author seems to be frustrated about is AGI is coming in computationally verifiable domains first, and lot of his skillset was taken over in a big part.
I have normally found any sort of timed technical competition intimidating. Even so, about 6 or 7 years ago, after being persuaded by a colleague, I participated in a few CTFs. I am glad I did, back when this type of thing still meant something. I have kept a screenshot from one of the CTFs that I am quite fond of: https://susam.net/files/blog/ctf-2019.png
«That feedback loop is breaking. If the visible scoreboard is dominated by teams using AI, a beginner is pushed toward using AI before they have built the instincts the AI is replacing. That is an anti-pattern. It prevents active learning, and active struggle is the bit that actually teaches you. It is also completely demotivating to put in real effort and see no visible progress because the ladder above you has been automated.»
This stands out to me, and speaks perhaps broader than the article itself? I’m sure this has been in the spotlight before, but well put for many areas I think.
I see this with beginner programming students at university. They get AI to help them with assignments, with the intention of learning, but ultimately they do not get the understanding they would have if they had done the assignment themselves. Then they are at a deficit for learning more advanced topics.
My fear is that they never get to the level they need to be at to create good software even with the help of AI. So, although an expert with AI can create great software, that is not where we end up. In stead we will have vibe coded messes by people who barely have any grasp of what is going on.
No, the search space is much more vast and the feedback loop almost nonexistent.
The reason LLMs can do CTFs so well is partially because the challenges are usually designed to avoid wasting time and to introduce a single concept without noise.
I can't help but draw parallels with video games. Aimbots in competitive multiplayer games is a well defined issue: it's considered cheating and frowned upon, players caught cheating are banned from the game. Tool-assisted speedruns (TAS) where a player attempts a world record at completion in a single-player game is another face of the same concept (computers help you win), but one that is socially accepted as long as runs are clearly labelled as TAS.
The biggest difference would be the fact that you can discover video game cheating through some kind of trace. Speed running communities go pretty hardcore on that kind of thing nowadays.
It's a lot harder to detect cheating when your only trace is how fast someone submitted the string CTF{DUck1e_Pwned}
Sure if the goal is entertainment and sports, you're right. However, unlike chess or counter strike it's downstream from a real needed utility. Like, is there a point to do it anymore? (ofc there is, but still, it's been devalued from the perspective of the 'real utility')
I don't do CTF's but took part at the security workshop for fun ~2 years with my Android phone only. I was first with the first simple challenge, but then couldnt continue because my phone was just too limited. But I watched what the others did. And a young Indian guy did everything with ChatGPT then. I found it silly, but amusing, because he actually got second. There was no Codex nor Claude then. Nowadays it must be dead for real, because I would solve everything with my agents, as I do in the real world.
I don’t think CTFs are dead, they’ll just evolve. The difficulty level will need to be increased or the rules locked down. Just like sports and racing persist despite the existence of performance enhancing drugs and rocket technology.
I just did a CTF where I was in the top 10. It was the first CTF I completed and I used AI because the rules permitted it. That said, I couldn’t solve all challenges.
But yes, it was significantly easier now than I last attempted one. Even manually solving with AI assisted assembly interpretation was much easier.
Increasing the difficulty level is a terrible solution. The problem with CTFs isn't that they're too easy. Making them harder just makes them even less accessible to people who don't cheat. It'd be like seeing people who put hidden electric motors in their bikes during Tour de France and conclude, "oh we just need longer distances and steeper hills".
LLMs don't tend to help much when solving challenges beyond their skill level. Either they one-shot a challenge, or thei are almost useless as a companion for them.
That doesn't work. The thing that made CTFs fun is the fact that the challenges are solvable in a short-ish timeframe, usually a day at most, if you have the requisite skills and talent.
The first paragraph on anything with an acronym in it should explain the bloody acronym. I assumed CTF was an encryption standard, given the headline. It was only coming here and reading the comments that made me realise it's a game-format ("Capture The Flag").
You can still do competitions. But you'll all need to fly to the same place and work on laptops with a fresh install of Linux. 1 hour to install tooling then Internet off, challenge revealed.
It is a hard requirement. Once you reach higher levels of challenges you spend most of your time reading through RFCs, web sepcs, Github issues, mailing lists, papers, random bugtrackers and library/framework code. There is no way to create a whitelist for that. Besides, a firewall won't stop good hackers.
Normal CTF workflows can involve a lot of research but that's not the point. You can design self-contained challenges with offline solving in mind, and bundle any truly necessary docs/src/etc. with the challenge download.
Do CTFs like Lan parties or factor in new tooling avalable to people. change is not death. or death is not an end. either way, people will enjoy applying and showing off their skill. competing with eachother on a human level,.with or without ai tools.
I think soon there will be ways to trick this models and I think when it happens it will be yet another layer like aslr
These models seems completely unbeatable only in the ads. There are 100+ times way someone puts Hindi Yoda talk In Morse Code and it goes nuts.
The reason they are going to hard for PR Marketing on this is because they know it is a matter of time.
The more you obfuscate a topic against LLMs the lower the educational value of a challenge.
The only things that works is novelty and obscurity. LLMs still suck with things mentioned in the footnotes of datasheets and manuals, things that deviate in subtle ways, unique constructions that alter something very very common. It's hard for LLMs to avoid common pitfalls in terms of making assumptions, while staying on track.
Capture The Flag is a cybersecurity game where the organizers set up a bunch of intentionally vulnerable computer systems with a "flag" on them, a string that's "supposed to be" secret but is accessible through exploiting the vulnerabilities. This may be a line in /etc/password, a string in memory, a field in a database, whatever. The goal of the game is to hack into the computer systems, find ("capture") the flag, then copy/paste it into the organiser's scoreboard website to prove that you solved that particular challenge.
It's pretty fun. Or at least it was, back when you had some sense that your competitors were competing on an even playing field and just beat you because they were better than you.
I wouldn't say the name is a "gaming reference", it's just a descriptive name for a game.
>If adaptation means accepting that the scoreboard is now an AI orchestration benchmark, then we should say that honestly instead of pretending the old competition still exists.
This is like someone complaining that making machine parts has been ruined: Skillful craftsmen used to make them by hand using manual tools!
Nowadays the CAD/CAM/CNC cheaters have almost completely automated the whole thing. How is the next generation of craftsmen going to learn how to craft a gear by hand when the process of gear making has been reduced to pressing start on a CNC machine?!
See what I mean? Sorry, I think this article is just Luddite. I can empathize with the pain of your beloved craft basically being rendered obsolete by new technology, but the process can neither be stopped nor is it bad in general.
The manual skills you trained with CTF puzzles are now simply no longer relevant . (Field-specific) "AI orchestration" is the new cyber securtiy skill if LLMs really have become so good at this, and what the author used to do manually then has the same value as being able to craft a gear by hand.
The way I read the post is that the author is disappointed that the community is gone. The CTF was just a reason for a number of like-minded people to organize around an activity.
Indeed, in the real world, plenty of people organize to do formerly-skillful tasks together. I have not personally crafted a gear by hand, but I have built a house in a long-abandoned style with a group of people only using hand tools.
There _is_ a danger that society forgets how to do these things. During that house-building exercise, there were many tricks of the trade that, while likely documented somewhere in a book, would have been difficult to reproduce without seeing a demonstration. From the standpoint of “does it matter?” it depends on what you care about. We absolutely do not need cruck-framed houses with scribed joints. Modern construction is faster and cheaper and lasts long enough. But it would sadden me greatly if practices like this faded from memory, because it’s one of those things that makes you gasp “wow!” when you see it. And your appreciation only deepens when you try it yourself.
Great article, well written, and good analogy to chess. I’ve been playing competitive chess most of my adult life and I think that the solution lies in how chess dealt with this problem:
Explicit ELO measurements with some cheating detection. AI assistance wholly banned. As you climb the ELO ladder, detection gets more onerous. At top level during online events, anti cheating teams require the use of both monitoring software and multiple cameras.
Idea is that you can cheat pretty easily at the lowest levels but it gets less easy the higher you go. This allows for better feeding into the truly elite competitions.
I think chess’s very firm stance that AI is never allowed in competition (neither online nor in person), rather than CTF’s acceptance, was the right call.
Interesting and well written article that mirrors/foreshadows how LLMs do and will change other scenes.
As I don't know much about the CTF scene, I looked for other takes on this topic.
Here's an article from 2015 about how tool-assistance already changed CTFs:
> Individual skill will undoubtedly be a factor next year. But, I'm left wondering whether next year's DEFCON CTF will tell us anything more than how well-developed each team's tools are (and how well they can interpret the results).
And here's someone explaining how Claude Max allowed them to win CTFs:
> I had always been interested in CTF as one of the only ways people could compete and show off their skill in coding/problem solving on a global scale. It was just too difficult and didn't make sense for me to learn the fundamentals as an electrical engineer. As time went on, I got better and better, and it was hard to tell whether it was because of experience or if it was because of improvements in AI.
> I accomplished my goals, and for that reason I'm quitting CTF, at least for now. [...] I'd like to think I highlighted the problem before it became a bigger issue. So, how do we fix this? Teams and challenge authors losing motivation is not good. CTF dying is not good. AI bad. Or is it?
The only article that saw LLMs as a non-negative force for CTFs was this one. Fittingly, it sounds like LLM output ("Let's be honest", "This is where things get interesting.") and only contains hallucinated references.
LLMs managing the "coloring book" equivalent of something is not bullish for the "art" version of something.
The intent for most CTFs is to provide a meaningful challenge that concerns a single topic without introducing noise that wastes time. Of course a training exercise is easier to complete for an LLM.
I'm conflicted on the use of AI in CTFs. On the one hand, they are supposed to mirror real-life scenarios, so of course you should be able to use any tool that would be available to you in real life.
On the other hand, CTFs are fundamentally a game and a competition which are supposed to be fun and compare and improve ones skill. So when I let an LLM generate the entire solution for me, what's the point anymore? I did not learn anything. I did not work for that place on the leaderboard, I just copied the solution. And worst of all, I did not have any fun. It's boring.
So how does using AI as a solver not feel like cheating?
These examples that you're calling "verbs as a noun" are standard grammar. You can't just invent simplified rules about a language and declare it wrong when the rules fall apart.
I helped arrange my country's longest living CTF this year. Our CTF is *made for amateurs*, but we always have challenges for intermediate to skilled players and the top of the scoreboard is usually topped by them. It is the compromise we have - amateurs get so many tasks they struggle to solve them all, and the pro's get to win. Our goal is to nerdsnipe people who are curious into trying our CTF by offering easy beginner tasks, and then get them hooked enough to stick around for the intermediate ones, even if it takes them a day to solve one.
This year, multiple groups on the top of the leaderboard were clearly abusing LLMs. You can tell because they know nothing of what a CTF is nor the terminology, nor really the fields the challenges were about when they were talked to. They were obviously amateurs.
It was pretty depressing to hear how unaware they were of how obviously they did not fit in to the type that usually is on the top of the leaderboard. It seems they seriously think they were under the radar. If it was one group it could be a freak incident - some times someone just shows up and curbstomps competition. But there were many groups like this this year. They also had a certain smugness to it - one staff reported that a group was hinting to other teams about their "super weapon". Another group credited their "secret third team member they didn't want to talk about".
I use LLM frequently and experiment with it a lot, both at work and on my free time. Nowadays they are good enough to have value and I am interested in learning more about that. They let me spend more time on hard problems and avoid spending the day on simple CRUD. I say this to say that LLM doesnt have to equal bad, it is a tool, that's all. However, I generally avoid LLM communities because many LLM fans are lazy and unskilled people who are just happy they can feel they are worth something even if they have no skill. They don't really have much to provide of conversation. If anything, from reading the CTF crowd this year, the rise of LLMs has just meant more of these people can stomp on and harvest the CTF scene for self validation.
This is not me trying to gatekeep who can play CTF. Anyone is welcome, but there is one condition: You are here to learn and have fun.
The conclusion many I talk to has come to is that nowadays, it is harder to learn to put in hard work and become good at something because there are just too many ways to cheat and take shortcuts. I suspect in the future there will be a shortage of useful people - the kind that have critical thought and know the value of doing something properly. This doesn't mean "Not using LLM", but as said by many on HN before you need a certain seniority before LLMs are useful augmentations to your skills and not just stopping you from learning yourself.
I agree with the article. Anything but physical competitions with strong security - think professional e-sports with organizer-provided PCs, is over.
My first ever was Stripe CTF in 2012 I think, I still wear the shirt I got (now super fainted) from passing some challenges.
I was a student in portugal and remember receiving the shirt for it and thinking, maybe those Americans aren't any better than me and I can compete at the same level.
I never got super into security but it gave me the confidence to play in the same field and lose the stupid aura I had that somehow "rich americans" would be better than me at everything because they had better universities or because of Hollywood or something.
Sad that another cool thing is lost to AI but I guess kids will learn in other ways.
Well, I had to google what CTF means (capture the flag, a hacking competition), so surely cannot judge here, but the text indicates that with AI some things are very different today:
"That makes open CTFs pay-to-win. The more tokens you can throw at a competition, the faster you can burn down the board. Specialised cybersecurity models like alias1 by Alias Robotics are becoming less relevant compared to general frontier LLMs. The competition is turning into "who can afford to run enough agents, with enough context, for long enough.""
1) It’s OK to do just about anything to win a CTF, including installing malware on the organisers computers months before the actual event so you’ll have an easy time stealing the flags.
2) It’s not ok to try and win the CTF with a solution the authors did not intend.
Recently the #2 crowd has been winning because the hacking scene has turned corporate and boring. People started to partake in CTFs in the hopes of landing a job(!)
CTFs are indeed ruined for those people, I personally don’t mind.
For the people in group #1 LLMs change little. Attacking the challenges directly was always a last resort.
I started playing in 2015 or so and had mostly stopped by 2020. Not because I felt it was "dead" exactly but it just wasn't hitting the same for me. By then it wasn't "the winner has the most LLMs", but "the winner has the most members on their team". I merged into one of the mega-teams and it just wasn't fun any more.
And if you think it was too long, what part would you have shortened? I never knew about the scene and found it interesting to read this personal take on it.
The only way this actually works is if you move CTF to in-person only. There's no other way to reasonably prevent the whole leaderboard being taken up by whoever spent the most on tokens.
"new" does the same thing and is probably just a better descriptor then frontier
"Frontier models break the open CTF format" is good
"Frontier AI..." means wtf is Frontier AI.
Because of course it exists (just googled it): https://frontierai.company/
We’ve figured out the human replacement pipeline it seems, but we haven’t figured out the eduction part. LLMs can be wonderful teachers, but the temptation to just tell it ‘do it for me’ is almost impossible to resist.
We usually hire for problem solving capabilities and not so much for technical know-how.
That’s at least how I read your comment.
If you remove the "without AI" and the end, I've been hearing similar anecdotes about fizzbuzz for years (isn't the whole point of fizzbuzz to filter out those candidates?)
But he was a great teacher anyway. He was engaging and kept the kids in line and learning. I eventually learned the truth, and most of my classmates forgot about it. Teaching, like flying a plane or driving a train, might become more about keeping watch over a small group of people and ensuring that things don't go off the rails, and that's fine.
I think it helps that it's a very narrow field to look at, compared to fuzzy and big-picture view of social studies, for example. So much room to be confidently wrong... And sadly I can't think of a solution, LLMs or not.
A Physics Prof Bet Me $10,000 I'm Wrong
https://www.youtube.com/watch?v=yCsgoLc_fzI
All things I learned in school which were wrong information.
Not to mention, the current state of education is far worse. I don't think most realize how low the bar is.
We can all agree that both human "experts" and LLMs can sometimes be right, and sometimes be confidently wrong.
But that doesn't imply that they're equally fit for purpose. It just means that we can't use that simple shortcut to conclude that one is inferior to the other.
So where do we go from here?
[0] Episode webpage: https://share.transistor.fm/s/31855e83
Are they or aren't they
Now I’m certain that there exist those mythical human instructors who can do better, but that’s not worth much if 99.99% of people don’t have access to them. Just like a good human physician who takes their time with the patient is better than an LLM, but that’s not worth much either given that this doesn’t match most people’s experience with their own physicians.
For me the best human teachers were the ones that managed to make me interested on topics that I thought are boring/useless (many times my opinion being stupid, mostly due to lack of experience).
So far with LLM I learn about things I know something (at least that they exist) and I am interested in, which is a small subset of things that one should learn during lifetime.
The kids learnt all about Team Fortress 2, Roblox, Rainbow Six etc. They also learnt how to game the learning system so it looked like they were doing their work.
Also, you could spin up your own educational agent with very strict instructions on guiding the user instead of just doing the work. Of course you can always go around it but if you're making an effort to learn, this is a good middle ground.
The solution is just to make CTFs harder, but when do CTFs become too hard? Maybe the problem is that 'hard' CTFs are fundementally too 'simple' where it's just a logic chain and an exhaustive bruteforce towards a solution since there really are limited ways to express a solution in plain sight.
Or maybe human creativity has been exhausted and we're not so limitless as we thought. Only time will tell.
I had another idea spring to mind: we could hide two flags, one that could only be found by ai agents and not humans or tools written by humans.
we have very powerful simulation tools so something like "project a pattern at these angles" wouldn't really work as you could simulate that.
I guess something cool is that we can make simulating the solution very expensive, but in real world it would be free since it's analog... As long as simulations take longer than it takes for a human to find a solution it would be a pretty good way to deal with it. I am sure people smarter than me can come up with something.
Maybe I was too early to dismiss human creativity.
There are a million places where a computer can interact with a non-digital system in a loop.
- Tune an FPGA, or a whole data-center, or just a physical computer.
- Make a drone fly somewhere.
- Design a selective toxin (or anti-toxin).
Or, you know, get more people to click on adds. All totally possible to automate.
You could even go so far that anything loaded on your computer is fair game, but not more than that (certain competitive programming competition for example allow unlimited amount of paper material - for CTFs you probably need much more than that, therefore electronic).
The same article talks about CTF skills as a way to learn about security best practices and separately a sport.
In reality it was all about learning an extremely important skillset (securing/attacking software and systems) that is getting automated.
The real thing the author seems to be frustrated about is AGI is coming in computationally verifiable domains first, and lot of his skillset was taken over in a big part.
This stands out to me, and speaks perhaps broader than the article itself? I’m sure this has been in the spotlight before, but well put for many areas I think.
My fear is that they never get to the level they need to be at to create good software even with the help of AI. So, although an expert with AI can create great software, that is not where we end up. In stead we will have vibe coded messes by people who barely have any grasp of what is going on.
The reason LLMs can do CTFs so well is partially because the challenges are usually designed to avoid wasting time and to introduce a single concept without noise.
It's a lot harder to detect cheating when your only trace is how fast someone submitted the string CTF{DUck1e_Pwned}
I just did a CTF where I was in the top 10. It was the first CTF I completed and I used AI because the rules permitted it. That said, I couldn’t solve all challenges.
But yes, it was significantly easier now than I last attempted one. Even manually solving with AI assisted assembly interpretation was much easier.
still has no mention of AI, but that will likely change as they increasingly dominate competition.
Not as easy logistically...
These models seems completely unbeatable only in the ads. There are 100+ times way someone puts Hindi Yoda talk In Morse Code and it goes nuts. The reason they are going to hard for PR Marketing on this is because they know it is a matter of time.
The only things that works is novelty and obscurity. LLMs still suck with things mentioned in the footnotes of datasheets and manuals, things that deviate in subtle ways, unique constructions that alter something very very common. It's hard for LLMs to avoid common pitfalls in terms of making assumptions, while staying on track.
It's pretty fun. Or at least it was, back when you had some sense that your competitors were competing on an even playing field and just beat you because they were better than you.
I wouldn't say the name is a "gaming reference", it's just a descriptive name for a game.
Its a war game reference I guess?
This is like someone complaining that making machine parts has been ruined: Skillful craftsmen used to make them by hand using manual tools!
Nowadays the CAD/CAM/CNC cheaters have almost completely automated the whole thing. How is the next generation of craftsmen going to learn how to craft a gear by hand when the process of gear making has been reduced to pressing start on a CNC machine?!
See what I mean? Sorry, I think this article is just Luddite. I can empathize with the pain of your beloved craft basically being rendered obsolete by new technology, but the process can neither be stopped nor is it bad in general.
The manual skills you trained with CTF puzzles are now simply no longer relevant . (Field-specific) "AI orchestration" is the new cyber securtiy skill if LLMs really have become so good at this, and what the author used to do manually then has the same value as being able to craft a gear by hand.
Indeed, in the real world, plenty of people organize to do formerly-skillful tasks together. I have not personally crafted a gear by hand, but I have built a house in a long-abandoned style with a group of people only using hand tools.
There _is_ a danger that society forgets how to do these things. During that house-building exercise, there were many tricks of the trade that, while likely documented somewhere in a book, would have been difficult to reproduce without seeing a demonstration. From the standpoint of “does it matter?” it depends on what you care about. We absolutely do not need cruck-framed houses with scribed joints. Modern construction is faster and cheaper and lasts long enough. But it would sadden me greatly if practices like this faded from memory, because it’s one of those things that makes you gasp “wow!” when you see it. And your appreciation only deepens when you try it yourself.
Explicit ELO measurements with some cheating detection. AI assistance wholly banned. As you climb the ELO ladder, detection gets more onerous. At top level during online events, anti cheating teams require the use of both monitoring software and multiple cameras.
Idea is that you can cheat pretty easily at the lowest levels but it gets less easy the higher you go. This allows for better feeding into the truly elite competitions.
I think chess’s very firm stance that AI is never allowed in competition (neither online nor in person), rather than CTF’s acceptance, was the right call.
As I don't know much about the CTF scene, I looked for other takes on this topic.
Here's an article from 2015 about how tool-assistance already changed CTFs:
> Individual skill will undoubtedly be a factor next year. But, I'm left wondering whether next year's DEFCON CTF will tell us anything more than how well-developed each team's tools are (and how well they can interpret the results).
https://fuzyll.com/2015/ctf-is-dead-long-live-ctf/
But there are quite a few recent (2026) articles with the same core message as in the original article, e.g., https://blog.includesecurity.com/2026/04/ctfs-in-the-ai-era/ or https://k3ng.xyz/blog/ctf-is-dead
And here's someone explaining how Claude Max allowed them to win CTFs:
> I had always been interested in CTF as one of the only ways people could compete and show off their skill in coding/problem solving on a global scale. It was just too difficult and didn't make sense for me to learn the fundamentals as an electrical engineer. As time went on, I got better and better, and it was hard to tell whether it was because of experience or if it was because of improvements in AI.
> I accomplished my goals, and for that reason I'm quitting CTF, at least for now. [...] I'd like to think I highlighted the problem before it became a bigger issue. So, how do we fix this? Teams and challenge authors losing motivation is not good. CTF dying is not good. AI bad. Or is it?
https://blog.krauq.com/post/ctf-is-dying-because-of-ai
The only article that saw LLMs as a non-negative force for CTFs was this one. Fittingly, it sounds like LLM output ("Let's be honest", "This is where things get interesting.") and only contains hallucinated references.
https://caverav.cl/posts/ctfs-not-dead/ctfs-not-dead/
I've seen that exact font and color scheme a dozen of times the past weeks.
The intent for most CTFs is to provide a meaningful challenge that concerns a single topic without introducing noise that wastes time. Of course a training exercise is easier to complete for an LLM.
What am I missing here?
Its not really a good comparison
On the other hand, CTFs are fundamentally a game and a competition which are supposed to be fun and compare and improve ones skill. So when I let an LLM generate the entire solution for me, what's the point anymore? I did not learn anything. I did not work for that place on the leaderboard, I just copied the solution. And worst of all, I did not have any fun. It's boring.
So how does using AI as a solver not feel like cheating?
Why so pedantic?
It's an incredibly exciting time in security research in my humble old man opinion.
Think the cadence of new exploits is perhaps a good measure of that rather than subjective thoughts by anyone regardless of experience.
This year, multiple groups on the top of the leaderboard were clearly abusing LLMs. You can tell because they know nothing of what a CTF is nor the terminology, nor really the fields the challenges were about when they were talked to. They were obviously amateurs.
It was pretty depressing to hear how unaware they were of how obviously they did not fit in to the type that usually is on the top of the leaderboard. It seems they seriously think they were under the radar. If it was one group it could be a freak incident - some times someone just shows up and curbstomps competition. But there were many groups like this this year. They also had a certain smugness to it - one staff reported that a group was hinting to other teams about their "super weapon". Another group credited their "secret third team member they didn't want to talk about".
I use LLM frequently and experiment with it a lot, both at work and on my free time. Nowadays they are good enough to have value and I am interested in learning more about that. They let me spend more time on hard problems and avoid spending the day on simple CRUD. I say this to say that LLM doesnt have to equal bad, it is a tool, that's all. However, I generally avoid LLM communities because many LLM fans are lazy and unskilled people who are just happy they can feel they are worth something even if they have no skill. They don't really have much to provide of conversation. If anything, from reading the CTF crowd this year, the rise of LLMs has just meant more of these people can stomp on and harvest the CTF scene for self validation.
This is not me trying to gatekeep who can play CTF. Anyone is welcome, but there is one condition: You are here to learn and have fun.
The conclusion many I talk to has come to is that nowadays, it is harder to learn to put in hard work and become good at something because there are just too many ways to cheat and take shortcuts. I suspect in the future there will be a shortage of useful people - the kind that have critical thought and know the value of doing something properly. This doesn't mean "Not using LLM", but as said by many on HN before you need a certain seniority before LLMs are useful augmentations to your skills and not just stopping you from learning yourself.
I agree with the article. Anything but physical competitions with strong security - think professional e-sports with organizer-provided PCs, is over.
I never got super into security but it gave me the confidence to play in the same field and lose the stupid aura I had that somehow "rich americans" would be better than me at everything because they had better universities or because of Hollywood or something.
Sad that another cool thing is lost to AI but I guess kids will learn in other ways.
>and the old game is not coming back
For many people the CTF scene was already dead in 2021 because it had turned into something unrecognisable.
In reality it’s just different.
"That makes open CTFs pay-to-win. The more tokens you can throw at a competition, the faster you can burn down the board. Specialised cybersecurity models like alias1 by Alias Robotics are becoming less relevant compared to general frontier LLMs. The competition is turning into "who can afford to run enough agents, with enough context, for long enough.""
1) It’s OK to do just about anything to win a CTF, including installing malware on the organisers computers months before the actual event so you’ll have an easy time stealing the flags.
2) It’s not ok to try and win the CTF with a solution the authors did not intend.
Recently the #2 crowd has been winning because the hacking scene has turned corporate and boring. People started to partake in CTFs in the hopes of landing a job(!)
CTFs are indeed ruined for those people, I personally don’t mind.
For the people in group #1 LLMs change little. Attacking the challenges directly was always a last resort.
Hits different doesn't it
The text itself being exceedingly long for no obvious reason doesn’t help.
And if you think it was too long, what part would you have shortened? I never knew about the scene and found it interesting to read this personal take on it.
According to Pikka, the paragraph text is Taupe Grey (#92908a) on a Liquorice (#111110) background. That's... pretty far from black and white.
The whole point of competitions is to provide a safe environment thanks to a set of rules all participants AGREE on in order to progress together.
If new tools "break" the competition, we change the rules and that's A-OK.
CTF isn't a natural phenomenon, if tools change, rules change, simple.